Application architectures become increasingly complex thanks to paradigms like microservices and containerization.
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Platform engineers design, build, and maintain the infrastructure and tools necessary for software development and deployment. They’re often the unsung heroes behind the digital curtain, enabling infrastructure automation and providing self-service capabilities to allow developers and product teams to expedite application delivery and provide customer value faster.
As application architectures become increasingly complex thanks to paradigms like microservices, containerization, and system distribution across different infrastructure types, platform engineers across the board face some common challenges and hurdles in ensuring developers and product owners have what they need to meet their productivity goals.
Platform engineers grapple with managing configurations and policies across diverse infrastructure types, especially in hybrid and multi-cloud architectures. With DevOps and CI/CD, they also bear the responsibility of maintaining a coherent state across different stages of development, testing, and production. Simple differences like JSON and YAML configurations can lead to inconsistencies, demanding expertise and a deep understanding of distributed systems across various environments. While implementing Infrastructure as Code (IaC) and automation tools like Ansible can help streamline the process of repeating the same configuration steps consistently across different environments, multiple tools, strategies and best practices are involved in effective infrastructure provisioning and management, creating further challenges for the platform teams.
With so many platform engineering tools and technologies available in the market, choosing the right ones for particular needs and ensuring compatibility across the entire multi-cloud environments can be daunting for platform engineers. They must choose between setting up vendor-neutral technologies like Kubernetes, Terraform, GitLab, and Ansible that require in-depth knowledge of potential incompatibilities or opt for platform-specific, end-to-end solutions like GKE and AKS and AWS CloudFormation and Azure ARM templates that may be simpler to use. However, being native to particular platforms, these services may not extend to other clouds in multi-cloud deployments and can tie organizations into vendor lock-in. Therefore, it’s as crucial as it is challenging for platform engineers to weigh in the benefits and assess the compatibility of the tools they choose to avoid running into issues down the line.
Platform engineers are constantly juggling performance, resources, and costs across complex multi-cloud setups. They must ensure high availability and performance while staying within the resource and budget restraints. This requires maintaining tight control and monitoring across all the cloud environments involved in the different phases of deployment, such as building, testing, staging and production. Multiple monitoring tools, each dedicated to a particular cloud in a multi-cloud environment, can add to the challenges of platform engineers. Theymust then deal with the silos between different platforms, the visibility gaps, and the need for managing several, disparate tools. Without complete and unified visibility into resource availability and utilization across the entire multi-cloud environment, platform engineers simply do not have the knowledge needed for cost optimizations.
Platform engineers must architect solutions that can seamlessly scale, horizontally across different regions or cloud providers based on growing demands. It involves implementing scalable infrastructure patterns with auto-scaling and load balancing capabilities that span multiple cloud environments. This can be hard to achieve as each provider has its own set of resources, data sources, and configurations specific to that provider. As such, platform engineers need to rely on tools like Terraform and Ansible to manage infrastructure and other cloud resources reliably and consistently across all clouds. While these tools provide a degree of abstraction, managing the differences between cloud providers, such as service capabilities, naming conventions, and feature variations, can still be challenging. Further abstractions and automation through cloud management platforms are paramount as manual intervention in multi-cloud scenarios can lead to errors,discrepancies and configuration drift.
Platform engineers need to implement fault-tolerant systems, keeping in mind redundancy and disaster recovery plans. This involves employing automated testing and robust monitoring systems for quick identification and resolution of emerging issues, like system failures, security breaches and performance issues. Planning redundancy and back ups across different on-premise and public cloud environments requires substantial expertise and deep knowledge of the available regions and resources across providers at any given time. In order to achieve this, platform engineers need a holistic view of their cloud environments to ensure applications and workloads are deployed strategically across different clouds to remain available at all times.
Here’s how the emma platform, a centralized and holistic cloud management application, enables platform engineers to overcome several aspects of the challenges mentioned above:
The emma platform provides a single dashboard for monitoring all cloud environments operating within an organization. The platform enables standardized, no-code configurations, simplifies resource provisioning, and streamlines the deployment process across any infrastructure environment. Platform engineers can choose the cloud or environment based on the unique needs of each stage within their CI/CD pipelines and leverage the emma platform’s abstractions and automation to ensure consistent policies and accurate configurations throughout.
The emma platform itself is vendor-agnostic and integrates with all major cloud providers and mainstream tools that platform engineers rely on. This simplifies decision-making for platform engineers that can choose the tools from a vetted list, reducing the complexity of evaluating compatibility and integrating different tools and technologies across their CI/CD pipelines.
The emma platform provides complete visibility into resource usage across multiple clouds, facilitating better analytics and optimal resource allocations. The emma platform leverages advanced AI and ML algorithms to highlight opportunities for resource conservation and cost optimizations across all cloud environments. Platform engineers can identify underutilized resources, idle or forgotten instances, and resource hogs to effectively implement resource optimization strategies.
The emma platform helps streamline the process of scaling workloads across multiple clouds by allowing platform engineers to set-up auto-scaling and load balancing policies. They can also find real-time offers and available spot instances across any region or provider to meet short-term demand hikes while staying on budget. The no-code approach to infrastructure management abstracts away differences between cloud providers and provides a consistent experience for platform engineers and DevOps.
The emma platform’s wizard allows platform engineers to transfer workloads and applications across regions and environments in just a few clicks. It lets them manage backup infrastructure through policies defined via the centralized dashboard and also allows them to opt for cross-provider backup replication.
By consolidating provisioning and management tasks, providing a unified view, and offering standardized tools and practices, the emma platform empowers platform engineers to efficiently navigate the complexities of managing multiple and complex infrastructure environments. They can centrally take charge of the entire environment without having to juggle multiple tools and platforms involved in the different stages of the software development lifecycle (SDLC) and CI/CD pipelines.
